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v0.9.0
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PharmCat committed Mar 25, 2021
1 parent b43dae1 commit ce91dc0
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2 changes: 1 addition & 1 deletion Project.toml
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@@ -1,7 +1,7 @@
name = "Metida"
uuid = "a1dec852-9fe5-11e9-361f-8d9fde67cfa2"
authors = ["Vladimir Arnautov <[email protected]>"]
version = "0.8.0"
version = "0.9.0"

[deps]
CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"
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4 changes: 4 additions & 0 deletions change.log
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@@ -1,3 +1,7 @@
v0.9.0
* remove redundant code
* change in nlopt solver keyword handling

v0.8.0
* BLAS syrk REML keyword
* documentation fix
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6 changes: 2 additions & 4 deletions src/fit.jl
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Expand Up @@ -50,10 +50,8 @@ function fit!(lmm::LMM{T};
if lmm.result.fit lmmlog!(io, lmm, verbose, LMMLogMsg(:INFO, "Refit model...")) end
lmm.result.fit = false

if solver == :nlopt
return fit_nlopt!(lmm; solver = :nlopt, verbose = verbose, varlinkf = varlinkf, rholinkf = rholinkf, aifirst = aifirst, g_tol = g_tol, x_tol = x_tol, f_tol = f_tol, hes = false, init = init, io = io)
elseif solver == :cuda
return fit_nlopt!(lmm; solver = :cuda, verbose = verbose, varlinkf = varlinkf, rholinkf = rholinkf, aifirst = aifirst, g_tol = g_tol, x_tol = x_tol, f_tol = f_tol, hes = false, init = init, io = io)
if solver != :default
return fit_nlopt!(lmm; solver = solver, verbose = verbose, varlinkf = varlinkf, rholinkf = rholinkf, aifirst = aifirst, g_tol = g_tol, x_tol = x_tol, f_tol = f_tol, hes = false, init = init, io = io)
end

if verbose == :auto
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2 changes: 1 addition & 1 deletion src/lmm.jl
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Expand Up @@ -142,7 +142,7 @@ function Base.show(io::IO, lmm::LMM)
continue
end
println(io, " Model: $(lmm.covstr.random[i].model === nothing ? "nothing" : string(lmm.covstr.random[i].model, "|", lmm.covstr.random[i].subj))")
println(io, " Type: $(lmm.covstr.random[i].covtype.s) ($(lmm.covstr.t[i])), Subjects: $(length(lmm.covstr.block[i]))")
println(io, " Type: $(lmm.covstr.random[i].covtype.s) ($(lmm.covstr.t[i])), Subjects: $(lmm.covstr.sn[i])")
#println(io, " Coefnames: $(coefnames(lmm.covstr.schema[i]))")
end
println(io, "Repeated: ")
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52 changes: 14 additions & 38 deletions src/varstruct.jl
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Expand Up @@ -399,8 +399,6 @@ struct CovStructure{T} <: AbstractCovarianceStructure
repeated::VarEffect
schema::Vector{Union{Tuple, AbstractTerm}}
rcnames::Vector{String}
# subject (local) blocks for each effect
block::Vector{Vector{Vector{UInt32}}}
# blocks for vcov matrix / variance blocking factor (subject)
vcovblock::Vector{Vector{UInt32}}
# number of random effect
Expand Down Expand Up @@ -436,7 +434,6 @@ struct CovStructure{T} <: AbstractCovarianceStructure
t = Vector{Int}(undef, alleffl)
tr = Vector{UnitRange{Int}}(undef, alleffl)
schema = Vector{Union{AbstractTerm, Tuple}}(undef, alleffl)
block = Vector{Vector{Vector{UInt32}}}(undef, alleffl)
z = Matrix{Float64}(undef, size(data, 1), 0)
subjz = Vector{BitMatrix}(undef, alleffl)
zrndur = Vector{UnitRange{Int}}(undef, alleffl - 1)
Expand All @@ -449,12 +446,12 @@ struct CovStructure{T} <: AbstractCovarianceStructure
#
sn = zeros(Int, alleffl)
if rn > 1
for i = 2:rn
@inbounds for i = 2:rn
if random[i].covtype.s == :ZERO error("One of the random effect have zero type!") end
end
end
# RANDOM EFFECTS
for i = 1:rn
@inbounds for i = 1:rn
if length(random[i].coding) == 0
fill_coding_dict!(random[i].model, random[i].coding, data)
end
Expand All @@ -467,9 +464,8 @@ struct CovStructure{T} <: AbstractCovarianceStructure
fillur!(zrndur, i, q)
fillur!(tr, i, t)

subjz[i] = modelcols(MatrixTerm(apply_schema(random[i].subj, StatsModels.schema(data, fulldummycodingdict(random[i].subj)))), data)
block[i] = makeblocks(subjz[i])

subjz[i] = convert(BitMatrix, modelcols(MatrixTerm(apply_schema(random[i].subj, StatsModels.schema(data, fulldummycodingdict(random[i].subj)))), data))
sn[i] = size(subjz[i], 2)
updatenametype!(ct, rcnames, csp, schema[i], random[i].covtype.s)
end
# REPEATED EFFECTS
Expand All @@ -480,9 +476,8 @@ struct CovStructure{T} <: AbstractCovarianceStructure
schema[end] = apply_schema(repeated.model, StatsModels.schema(data, repeated.coding))
rz = modelcols(MatrixTerm(schema[end]), data)

subjz[end] = modelcols(MatrixTerm(apply_schema(repeated.subj, StatsModels.schema(data, fulldummycodingdict(repeated.subj)))), data)
block[end] = makeblocks(subjz[end])

subjz[end] = convert(BitMatrix, modelcols(MatrixTerm(apply_schema(repeated.subj, StatsModels.schema(data, fulldummycodingdict(repeated.subj)))), data))
sn[end] = size(subjz[end], 2)
q[end] = size(rz, 2)
csp = covstrparam(repeated.covtype, q[end], repeated.p)
t[end] = csp[1] + csp[2]
Expand All @@ -507,15 +502,13 @@ struct CovStructure{T} <: AbstractCovarianceStructure
blocks = makeblocks(subjblockmat) #vcovblock
sblock = Vector{Vector{Vector{Vector{UInt32}}}}(undef, length(blocks))
########################################################################
for i = 1:length(blocks)
@inbounds for i = 1:length(blocks)
sblock[i] = Vector{Vector{Vector{UInt32}}}(undef, alleffl)
for s = 1:alleffl
@inbounds for s = 1:alleffl
sblock[i][s] = Vector{Vector{UInt32}}(undef, 0)
for col in eachcol(view(subjz[s], blocks[i], :))
#if any(col) push!(sblock[i][s], sort!(findall(x->x==true, col))) end
if any(col) push!(sblock[i][s], findall(x->x==true, col)) end
@inbounds for col in eachcol(view(subjz[s], blocks[i], :))
if any(col) push!(sblock[i][s], findall(col)) end
end
sn[s] += length(sblock[i][s])
end
end
#
Expand All @@ -524,7 +517,7 @@ struct CovStructure{T} <: AbstractCovarianceStructure
lvcb = length(i)
if lvcb > maxn maxn = lvcb end
end
new{eltype(z)}(random, repeated, schema, rcnames, block, blocks, rn, z, sblock, zrndur, rz, q, t, tr, tl, ct, sn, maxn)
new{eltype(z)}(random, repeated, schema, rcnames, blocks, rn, z, sblock, zrndur, rz, q, t, tr, tl, ct, sn, maxn)
end
end
################################################################################
Expand Down Expand Up @@ -597,23 +590,6 @@ function rcoefnames(s, t, ve)
return v
end
end

#=
function subjmatrix!(subj, data, subjz, i)
if length(subj) > 0
if length(subj) == 1
subjterm = Term(subj[1])
else
subjterm = InteractionTerm(Tuple(Term.(subj)))
end
subjdict = Dict{Symbol, AbstractContrasts}()
fill_coding_dict!(subjterm, subjdict, data)
subjz[i] = BitArray(modelcols(apply_schema(subjterm, StatsModels.schema(data, subjdict)), data))
else
subjz[i] = trues(size(data, 1),1)
end
end
=#
################################################################################
function makeblocks(subjz)
blocks = Vector{Vector{UInt32}}(undef, 0)
Expand All @@ -624,9 +600,10 @@ function makeblocks(subjz)
blocks
end
################################################################################
function noncrossmodelmatrix(mx::AbstractArray{T}, my::AbstractArray{T}) where T
function noncrossmodelmatrix(mx::AbstractArray, my::AbstractArray)
size(mx, 2) > size(my, 2) ? (mat = mx' * my; a = mx) : (mat = my' * mx; a = my)
#mat = mat * mat'
T = eltype(mat)
@inbounds for n = 1:size(mat, 2)-1
fr = findfirst(x->!iszero(x), view(mat, n, :))
if !isnothing(fr)
Expand Down Expand Up @@ -654,8 +631,7 @@ function noncrossmodelmatrix(mx::AbstractArray{T}, my::AbstractArray{T}) where T
end
end
res = replace(x -> iszero(x) ? 0 : 1, view(mat, :, cols))
result = a * res
result
a * res
end
################################################################################
# CONTRAST CODING
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@PharmCat
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Release notes:

v0.9.0

  • remove redundant code
  • change in nlopt solver keyword handling

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Registration pull request created: JuliaRegistries/General/32835

After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.

This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:

git tag -a v0.9.0 -m "<description of version>" ce91dc07649a4ea2c509680ea11f301ffd30a0e1
git push origin v0.9.0

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